TensorFlow Probability

TensorFlow Probability is a library for probabilistic reasoning and statistical
analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow
Probability provides integration of probabilistic methods with deep networks,
gradient-based inference via automatic differentiation, and scalability to
large datasets and models via hardware acceleration (e.g., GPUs) and distributed
computation.

Our probabilistic machine learning tools are structured as follows.

Layer 0: TensorFlow. Numerical operations. In particular, the LinearOperator
class enables matrix-free implementations that can exploit special structure
(diagonal, low-rank, etc.) for efficient computation. It is built and maintained
by the TensorFlow Probability team and is now part of
tf.linalg
in core TF.

Currently, TensorFlow Probability does not contain any GPU-specific code. The
primary difference between these packages is that tensorflow-probability-gpu
depends on a GPU-enabled version of TensorFlow.

To force a Python 3-specific install, replace pip with pip3 in the above
commands. For additional installation help, guidance installing prerequisites,
and (optionally) setting up virtual environments, see the TensorFlow
installation guide.

You can also install from source. This requires the Bazel build system.